Image processing device, image processing method, and program

ABSTRACT

An image processing device includes: a peripheral objective pixel random acquiring section acquiring pixels obtained by sampling peripheral pixels located in a periphery of a marked pixel which is marked at random with respect to the marked pixel of pixels corresponding to an objective image as an object of noise removal as peripheral objective pixels as pixels used for filtering for noise removal; and a noise removing section carrying out filtering for the noise removal by using the peripheral objective pixels.

BACKGROUND

The present disclosure relates to an image processing device, an imageprocessing method, and a program. In particularly, the disclosurerelates to an image processing device, an image processing method, and aprogram which can readily prevent reduction of an image quality, forexample, in noise removal for an image.

For example, as disclosed in Japanese Patent Laid-Open No. 2005-311455,a method of filtering image data by using a conditional average filtersuch as an ε filter is known as a noise removing filter for efficientlyremoving a noise contained in image data such as so-called RAW data.

With the ε filter, the noise is removed by averaging a flat portionwhile an edge of an image is maintained.

That is to say, with the ε filter, for example, pixels corresponding toan objective image as an object of the noise removal are successivelyselected as a marked pixel to which attention is paid. Also, ofperipheral pixels located in the periphery of the marked pixel, theperipheral pixels in each of which an absolute value of a difference inpixel value between corresponding one of the peripheral pixels and themarked pixel falls within a threshold value are each used as an objectof the averaging. Also, an average value of the pixel values of theperipheral pixels each becoming an object of the averaging are obtained(the peripheral pixels each becoming the object of the averaging areaveraged), and the resulting average value is used as a pixel value ofthe marked pixel.

For enhancing the effect of the noise removal by using the ε filter, itis known that it is effective to set an offset frequency of the ε filterat a low value.

Now, for example, when a high-sensitivity image is captured byhigh-speed image capturing (image capturing at a high-speed shutterspeed) with a digital camera (such as a digital still camera or adigital video camera), an image (low-S/N ratio image) in which aSignal-to-Noise Ratio (S/N ratio) is remarkably deteriorated is obtainedin some cases.

For the purpose of effectively removing the noise from the low-S/N ratioimage data, it is necessary that a range of the peripheral pixels usedfor the filtering by the ε filter is widened, and the filtering by the εfilter is carried out by using a large number of peripheral pixels.

However, when a large number of peripheral pixels are used for thefiltering by the ε filter, an amount of arithmetic operation requiredfor the filtering is increased, and a processing time and a hardwarescale are eventually increased.

Then, for example, a noise removing method is provided in JapanesePatent Laid-Open No. 2008-153917 (hereinafter referred to as PatentDocument 1). In this case, in the noise removing method, a part ofperipheral pixels is thinned out with a given pattern (a tap coefficientby which the pixel values of the pixels to be thinned out are multipliedis made zero, whereby the pixel values of the pixels by which the tapcoefficient is multiplied are substantially thinned out), and thefiltering by the ε filter is carried out by using the pixels after thetinning-out, in a word, a less number of peripheral pixels.

Here, when a part of the peripheral pixels is thinned out, and thefiltering by the ε filter is carried out by using the pixels after thetinning-out, a so-called artifact is generated in the image after thefiltering by the ε filter due to the thinning-out of the peripheralpixels, and thus the image quality is reduced.

In order to cope with such a situation, with the noise removing methoddisclosed in Patent Document 1, an image signal of an objective image isdivided into a low-frequency component and a high-frequency component interms of a band. In this case, for the image corresponding to thelow-frequency component, the filtering by the ε filter is carried out byusing the peripheral pixels after the thinning-out. On the other hand,for the image corresponding to the high-frequency component, thefiltering by a median filter is carried out. Also, the imagecorresponding to the low-frequency component after the filtering, andthe image corresponding to the high-frequency component after thefiltering are synthesized with each other, thereby obtaining theobjective image after the noise removal (post-noise removal image).

With the noise removing method disclosed in Patent Document 1, theperipheral pixels after the thinning-out used for the filtering by the εfilter are the pixels corresponding to the image signal containingtherein the low-frequency component. Therefore, it is possible tosuppress the artifact (the artifact of the high-frequency component ofthe objective image) generated in the image after the noise removal dueto the thinning-out of the peripheral pixels. Thus, it is possible toobtain the post-noise removal image in which the reduction of the imagequality due to the generation of the artifact is prevented.

SUMMARY

With the noise removing method as described above in which a part of theperipheral pixels is thinned out in accordance with the predeterminedpattern, and the filtering by the ε filter is carried out by using theperipheral pixels after the thinning-out, an amount of arithmeticoperation becomes less because the number of peripheral pixels used forthe filtering by the ε filter is small. However, for the purpose ofpreventing the reduction of the image quality due to the artifactgenerated in the post-noise removal image, it is necessary to divide theimage signal of the objective image into the low-frequency component andthe high-frequency component in terms of the band.

The band division of the image signal of the objective image into thelow-frequency component and the high-frequency component is carried outby using both of a Low-Pass Filter (LPF) and a High-Pass Filter (HPF).However, the LPF needs to be designed in such a way that the artifactcan be suitably suppressed, which is troublesome.

In addition, it is troublesome that the band division needs to benecessarily carried out in order to prevent the reduction of the imagequality of the post-noise removal image due to the generation of theartifact.

The present disclosure has been made in order to solve the problemsdescribed above, and it is therefore desirable to provide an imageprocessing device, an image processing method, and a program which canreadily preventing reduction of an image quality due to generation of anartifact in noise removal for an image.

In order to attain the desire described above, according to anembodiment of the present disclosure, there is provided an imageprocessing device including: a peripheral objective pixel randomacquiring section acquiring pixels obtained by sampling peripheralpixels located in a periphery of a marked pixel which is marked atrandom with respect to the marked pixel of pixels corresponding to anobjective image as an object of noise removal as peripheral objectivepixels as pixels used for filtering for noise removal; and a noiseremoving section carrying out filtering for the noise removal by usingthe peripheral objective pixels.

According to another embodiment of the present disclosure, there isprovided an image processing method including: acquiring pixels obtainedby sampling peripheral pixels located in a periphery of a marked pixelwhich is marked at random with respect to the marked pixel of pixelscorresponding to an objective image as an object of noise removal asperipheral objective pixels as pixels used for filtering for noiseremoval by an image processing device; and carrying out filtering forthe noise removal by using the peripheral objective pixels by the imageprocessing device.

According to still another embodiment of the present disclosure, thereis provided a program causing a computer to make a function so as toinclude: a peripheral objective pixel random acquiring section acquiringpixels obtained by sampling peripheral pixels located in a periphery ofa marked pixel which is marked at random with respect to the markedpixel of pixels corresponding to an objective image as an object ofnoise removal as peripheral objective pixels as pixels used forfiltering for noise removal; and a noise removing section carrying outfiltering for the noise removal by using the peripheral objectivepixels.

According to the embodiments of the present disclosure, the pixelsobtained by sampling the peripheral pixels located in the periphery ofthe marked pixel which is marked at random with respect to the markedpixel of the pixels corresponding to the objective image as the objectfor the noise removal are acquired as the peripheral objective pixels asthe pixels used for the filtering for the noise removal. Also, thefiltering for the noise removal is carried out by using the peripheralobjective pixels.

It is noted that the image processing device either may be anindependent device or may be an internal block composing one apparatusor device.

In addition, the program can be provided in such a way that the programis either transmitted through a transmission media or recorded in arecording media.

As set forth hereinabove, according to the present disclosure, thereduction of the image quality due to the generation of the artifact canbe readily prevented in the noise removal for the image.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing an entire configuration of a digitalcamera;

FIG. 2 is a block diagram showing a first configuration of a noiseremoving device as an image processing device according to a firstembodiment of the present disclosure;

FIG. 3 is a diagram explaining processing in a peripheral pixelacquiring section and a pixel thinning-out section including in thenoise removing device shown in FIG. 2;

FIG. 4 is a flow chart explaining noise removing processing;

FIG. 5 is a block diagram showing a second configuration of a noiseremoving device as an image processing device according to a secondembodiment of the present disclosure; and

FIG. 6 is a block diagram showing an example of a configuration of acomputer in which a program is installed.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Embodiments of the present disclosure will be described in detailhereinafter with reference to the accompanying drawings.

1. Entire Configuration of Digital Camera

FIG. 1 is a block diagram showing an entire configuration of a digitalcamera.

Referring now to FIG. 1, the digital camera includes an imaging element11, a preprocessing portion 12, an optical correcting portion 13, asignal processing portion 14, a codec portion 15, a recording controlportion 16, and a recording media 17.

The imaging element 11 is composed of a Charged Coupled Device (CCD), aComplementary Metal-Oxide Semiconductor (CMOS) imager, or the like. Theimaging element 11 photoelectrically converts an optical image formed onan imaging area by a lens unit (not shown) and outputs image signals aspixel values of Red, Green and Blue (RGB) of, for example, a Bayerarrangement.

The preprocessing portion 12 subjects the image signal outputted fromthe imaging element 11 to various kinds of processing such ascorrelation double sampling processing, automatic gain adjustingprocessing, Analog/Digital (A/D) conversion processing. Also, thepreprocessing portion 12 supplies RAW data as the resulting digitalimage data to the optical correcting portion 13.

The optical correcting portion 13, for example, is composed of a DigitalSignal Processor (DSP) or the like, and subjects the image data (RAWdata) supplied thereto from the preprocessing portion 12 to defectcorrecting processing, white balance adjusting processing, noiseremoving processing, and the like. Also, the optical correcting portion13 supplies the RAW data as the resulting image data to each of thesignal processing portion 14 and the recoding control portion 16.

The signal processing portion 14 subjects the image data suppliedthereto from the optical correcting portion 13 to de-mosaic processing,resolution converting processing, γ correction processing, image qualitycorrecting processing, and the like. Also, the signal processing portion14 outputs image data on a luminance signal and color differencesignals.

The image data outputted from the signal processing portion 14 issupplied not only to the codec portion 15, but also to a display device(not shown) such as a liquid crystal panel. The display device displaysthereon a so-called through image in correspondence to the image datasupplied thereto from the signal processing portion 14.

The codec portion 15 compresses the image data supplied thereto from thesignal processing portion 14 in accordance with a predetermined codingsystem and supplies the resulting compressed data to the recordingcontrol portion 16.

Here, when the image data supplied from the signal processing portion 14is image data on a still image, the codec portion 15 compresses theimage data supplied thereto from the signal processing portion 14 inaccordance with a coding system for a still image such as a JointPhotographic Coding Experts Group (JPEG). In addition, when the imagedata supplied from the signal processing portion 14 is image data on amoving image, the codec portion 15 compresses the image data suppliedthereto from the signal processing portion 14 in accordance with acoding system for a moving image such as a Moving Picture Experts Group(MPEG).

The recoding control portion 16 carries out recording control inaccordance with which the compressed data supplied from the codecportion 15, and the RAW data supplied from the optical correctingportion 13 are recorded in the recording media 17.

The recording media 17, for example, is a semiconductor memory such as amemory card, a disc-like recording media such as an optical disc or amagnetic disk (hard disk), or a tape-like recording media such as amagnetic tape. The image data is recorded in the recording media 17 inaccordance with the recording control made by the recording controlportion 16.

It is noted that either a recording media built in the digital camera ora recording media detachably installed in the digital camera, or both ofthem can be adopted as the recording media 17.

2. First Embodiment [First Configuration of Noise Removing Device]

FIG. 2 is a block diagram showing a first configuration of a noiseremoving device, as a portion (image processing device) for executingnoise removing processing according to a first embodiment of the presentdisclosure in the optical correcting portion 13 shown in FIG. 1.

Referring now to FIG. 2, the noise removing device includes a buffer 21,a marked pixel acquiring portion 22, a peripheral objective pixel randomacquiring portion 23, a noise removing portion 26, and a control portion27.

The image data (RAW data) from the preprocessing portion 12 is suppliedas image data on an objective image as an object of noise removal to thebuffer 21.

Here, hereinafter, for ease of a description, the objective image issupposed to be a still image.

The buffer 21, for example, is composed of plural line buffers, andtemporarily stores therein the image data on the objective imagesupplied thereto from the preprocessing portion 12.

The marked pixel acquiring portion 22 successively selects the pixelscorresponding to the objective image the image data on which is storedin the buffer 21, for example, in a raster scanning order as the markedpixel which is marked, and acquires the marked pixel by reading out thepixel value of the marked pixel from the buffer 21, and supplies thepixel value of the marked pixel thus read out to the noise removingportion 26.

Here, the control portion 27 which will be described later can supplythe information on a defect pixel(s) of the imaging element 11 (refer toFIG. 1) to each of blocks 21 to 26 composing the noise removing deviceas may be necessary.

The marked pixel acquiring portion 22 determines whether or not themarked pixel is the defect pixel in accordance with the information onthe defect pixel(s) supplied thereto from the control portion 27. Whenit is determined that the marked pixel is the defect pixel, the markedpixel acquiring portion 22, for example, adopts an average or the likeof plural pixel values of plural pixels each adjacent to the markedpixel as the pixel value of the marked pixel.

The peripheral objective pixel random acquiring portion 23 acquires thepixels obtained by sampling the peripheral pixels located in theperiphery of the marked pixel at random with respect to the marked pixelof the pixels, corresponding to the objective image, whose image valuesare stored in the buffer 21 by reading out the pixel values of thesepixels as the peripheral objective pixels as the pixels used for thefiltering for the noise removal. Also, the peripheral objective pixelrandom acquiring portion 23 supplies the pixel values of these pixelsthus acquired to the noise removing portion 26.

Here, referring to FIG. 2, the peripheral objective pixel randomacquiring portion 23 includes a peripheral pixel acquiring section 24and a pixel thinning-out section 25.

The peripheral pixel acquiring section 24, for example, sets aperipheral area as a rectangular area having a predetermined size withthe marked pixel as a center in accordance with the control made by thecontrol portion 27. Also, the peripheral pixel acquiring section 24acquires the pixels other than the marked pixel within the peripheralarea as the peripheral pixels located in the periphery of the markedpixel by reading out the pixel values of these pixels from the buffer21, and supplies the pixel values of these pixels thus acquired to thepixel thinning-out section 25.

The pixel thinning-out section 25 thins out the peripheral pixels bysampling the peripheral pixels whose pixel values are supplied theretofrom the peripheral pixel acquiring section 24. Also, the pixelthinning-out section 25 supplies the pixel values of the remainingperipheral pixels, in a word, the pixel values of the peripheral pixelsthus sampled as the pixel values of the peripheral objective pixels asthe pixels used for the filtering for the noise removal to the noiseremoving portion 26.

The noise removing portion 26, for example, is composed of a conditionalaverage filter such as the ε filter. Also, the noise removing portion 26carries out the filtering for the noise removal with respect to themarked pixel by using both of the pixel values of the marked pixelsupplied from the marked pixel acquiring portion 22, and the pixelvalues of the peripheral objective pixels supplied from the peripheralobjective pixel random acquiring portion 23. Also, the noise removingportion 26 outputs the resulting pixel value after the filtering as thepixel value of the marked pixel of the post-noise removal image obtainedby removing the noise from the image signal of the objective image.

That is to say, the noise removing portion 26, for example, is composedof a two-dimensional ε filter in which all of the tap coefficientsare 1. Also, with the noise removing portion 26 such as thetwo-dimensional ε filter, both of the marked pixel, and the peripheralobjective pixels in which absolute values of differences between thepixel values thereof and the pixel value of the marked pixel each fallwithin a predetermined threshold value are used as an object of weightedaveraging having the tap coefficient as a weight. Under this condition,a weighted average of the pixel values of the pixels as the object ofthe weighted averaging is obtained, and is used as the pixel value ofthe marked pixel of the post-noise removal image.

It is noted that since in this case, all of the tap coefficients of theε filter are 1, the weighted average obtained in the ε filter becomes anaverage value of the pixel values of the pixels as the object of theweighted averaging.

In addition, in this case, the ε filter in which all of the tapcoefficients are 1 is adopted as the noise removing portion 26. Inaddition thereto, however, a filter, such as another ε filter or abilateral filter, for carrying out the filtering for obtaining theconditional averaging of the pixel values of the pixels within a givenarea can also be adopted as the noise removing portion 26. In this case,in another ε filter, the larger value is obtained in the tap coefficientby which the pixel value of the pixel close to the marked pixel ismultiplied. Also, in the bilateral filter, the tap coefficient isdetermined in accordance with both of a distance, and a difference ofthe pixel value with the marked pixel.

The control portion 27 controls the blocks 21 to 26 composing the noiseremoving device.

That is to say, for example, the control portion 27 acquires theinformation on the defect pixel of the imaging element 11 (refer to FIG.1), and supplies the information thus acquired to the marked pixelacquiring portion 22 and the like.

In addition, for example, the control portion 27 controls (theperipheral pixel acquiring section 24 and the pixel thinning-out section25 of) the peripheral objective pixel random acquiring portion 23 inaccordance with a shutter speed of the digital camera (refer to FIG. 1).

Specifically, for example, when the shutter speed of the digital camerais set to a speed not being a high speed, that is to say, when theshutter speed of the digital camera is set to a value smaller than apredetermined threshold value such as a speed for the high-speed imagecapturing (the image capturing at a high shutter speed), the controlportion 27, for example, controls the peripheral pixel acquiring section24 so as to set a peripheral area having a predetermined size(hereinafter referred to as a default size as well) similar to the caseof the noise removing processing for the existing digital camera or thelike.

In addition, the control portion 27 sets a sampling pattern representingthe positions of all of the pixels (except for the marked pixel) withinthe peripheral area as a sampling pattern representing the positions(the relative positions with the position of the marked pixel as areference) of the pixels which are to be sampled at random. Also, thecontrol portion 27 supplies data on the sampling pattern thus set to thepixel thinning-out section 25.

Therefore, in this case, in the peripheral objective pixel randomacquiring portion 23, the peripheral pixel acquiring section 24 sets theperipheral area having the default size in accordance with the controlmade by the control portion 27. Also, the peripheral objective pixelrandom acquiring portion 23 acquires the pixel values of the pixelsother than the marked pixel within the peripheral area as the pixelvalues of the peripheral pixels located in the periphery of the markedpixel by reading out the pixel values of the pixels other than themarked pixel within the peripheral area from the buffer 21. Also, theperipheral objective pixel random acquiring portion 23 supplies thepixel values of the peripheral pixels thus acquired to the pixelthinning-out section 25.

Also, the pixel thinning-out section 25 samples the peripheral pixelswhose pixel values are supplied from the peripheral pixel acquiringsection 24 in accordance with the sampling pattern the data on which issupplied thereto from the control portion 27. Also, the pixelthinning-out section 25 supplies the pixel values of the peripheralpixels thus sampled as the pixel values of the peripheral objectivepixels to the noise removing portion 26.

In this case, in the pixel thinning-out section 25, all of theperipheral pixels whose pixel values are supplied from the peripheralpixel acquiring section 24, and the pixel values of all of theperipheral pixels are supplied as the pixel values of the peripheralobjective pixels to the noise removing portion 26.

Therefore, when the shutter speed of the digital camera is set to thespeed not being the high speed, and thus it is possible to expect theimage capturing of the image having the S/N ratio equal to or largerthan a certain degree, with the ε filter as the noise removing portion26, similarly to the case of the existing digital camera or the like,the filtering is carried out by using all of the pixels within theperipheral area having the default size.

On the other hand, when the shutter speed of the digital camera is setto the high speed, that is, when, for example, the shutter speed of thedigital camera is set to a value equal to or larger than thepredetermined threshold value such as the speed for the high-speed imagecapturing, and as a result, the possibility that an image in which theS/N ratio is remarkably deteriorated is obtained as the objective imageis high, for the purpose of effectively removing the noise from theimage signal of such an image in which the S/N ratio is remarkablydeteriorated, the control portion 27 controls the peripheral pixelacquiring section 24 so as to set the peripheral area having a sizelarger than the default size (hereinafter referred to as “a largesize”).

In addition, the control portion 27 selects the pixels having apredetermined rate such as ½ or ⅓ of the pixels (except for the markedpixel) within the peripheral area at random, and sets a sampling patternrepresenting the positions of the pixels thus selected, therebysupplying data on the sampling pattern thus set to the pixelthinning-out section 25.

Therefore, in this case, in the peripheral objective pixel randomacquiring portion 23, the peripheral pixel acquiring section 24 sets theperipheral area having the large size in accordance with the controlmade by the control portion 27. Also, the peripheral pixel acquiringsection 24 acquires the pixel values of the pixels other than the markedpixel within the peripheral area as the pixel values of the peripheralpixels located in the periphery of the marked pixel by reading out thepixel values of the pixels other than the marked pixel within theperipheral area from the buffer 21, thereby supplying the pixel valuesof the pixels other than the marked pixel within the peripheral area tothe pixel thinning-out section 25.

Here, in this case, the size of the peripheral area is the large size.Thus, when all of the pixels within such a peripheral area used for thefiltering in the noise removing portion 26, an amount of arithmeticoperation required for the filtering becomes large.

Then, the pixel thinning-out section 25 samples the peripheral pixelswhose pixel values are supplied thereto from the peripheral pixelacquiring section 24 (at random), and supplies the pixel values of theperipheral pixels thus sampled as the pixel values of the peripheralobjective pixels to the noise removing portion 26.

In this case, the sampling pattern represents the positions of thepixels having the predetermined rate and selected from the pixels withinthe peripheral area having the large size at random. With the pixelthinning-out section 25, the peripheral pixels having the predeterminedrate of the peripheral pixels whose pixel values are supplied from theperipheral pixel acquiring section 24 are sampled at random, and thepixel values thereof are supplied to the noise removing portion 26.

Therefore, when the shutter speed of the digital camera is set to thehigh speed, with the ε filter as the noise removing portion 26, thefiltering is carried out by using the peripheral pixels (peripheralobjective pixels) having the predetermined rate which are selected(sampled) from the peripheral pixels within the peripheral area havingthe large size at random.

Here, in the sampling pattern representing the positions of the pixelshaving the predetermined rate which are selected (sampled) from theperipheral pixels within the peripheral area having the large size atrandom, for example, (the number close to) the number of pixels withinthe peripheral area having the default size, or the like can be adoptedas the number of pixels having the predetermined rate.

In this case, with an amount of arithmetic operation similar to the casewhere the peripheral area having the default size is set as theperipheral area, that is, the noise can be effectively removed from theimage signal of the objective image in which the S/N ratio is remarkablydeteriorated while an increase in amount of arithmetic operation issuppressed.

It is noted that an operation mode when the shutter speed of the digitalcamera is set to the speed not being the high speed is referred as adefault mode, and an operation mode when the shutter speed of thedigital camera is set to the high speed is referred as a high-speed modeas well.

Since the operation in the default mode is the same as that of theexisting digital camera, in the following description, a description ofthe defect mode is omitted and a description of the high-speed mode isgiven unless otherwise stated.

[Description of Processing in Peripheral Objective Pixel RandomAcquiring Portion 23]

FIG. 3 is a diagram explaining processing in the peripheral pixelacquiring section 24 and the pixel thinning-out section 25 (in a phaseof the high-speed mode) composing the peripheral objective pixel randomacquiring portion 23 shown in FIG. 2.

As described above, the peripheral pixel acquiring section 24 sets theperipheral area having the large size in accordance with the controlmade by the control portion 27. Also, the peripheral pixel acquiringsection 24 acquires the pixel values of the peripheral pixels as thepixels (other than the marked pixel) within the peripheral area byreading out the pixel values of the peripheral pixels as the pixelswithin the peripheral area from the buffer 21, and supplies the pixelvalues of the peripheral pixels thus read out to the pixel thinning-outsection 25.

Referring to FIG. 3, a certain pixel is selected as the marked pixel,and an area having the pixels of 7×7 with the marked pixel as a centeris set as the peripheral area having the large size. Also, the pixelvalues of the peripheral pixels as the pixels within the peripheral areahaving the large size are acquired, and are then supplied to the pixelthinning-out section 25.

In addition, after that, the pixel on an immediate right-hand side ofthe marked pixel is selected as a new marked pixel, and this isrepetitively followed by the same processing.

The pixel thinning-out section 25 samples the peripheral pixels whosepixel values are supplied thereto from the peripheral pixel acquiringsection 24 in accordance with the sampling pattern from the controlportion 27. Also, the pixel thinning-out section 25 supplies the pixelvalues of the peripheral pixels obtained through the sampling as thepixel values of the peripheral objective pixels to the noise removingportion 26.

Here, as described above, with the control portion 27, the pixels havingthe predetermined rate within the peripheral area having the large sizeare selected at random, and the sampling pattern representing thepositions of the pixels obtained through the random selection is set.Therefore, as a result, with the pixel thinning-out section 25, of theperipheral pixels whose pixel values are supplied from the peripheralpixel acquiring section 24, the peripheral pixels having thepredetermined rate are sampled at random and the pixel values thereofare supplied as the pixel values of the peripheral objective pixels tothe noise removing portion 26.

Also, with the noise removing portion 26, the filtering is carried outnot by using all of the pixel values of the peripheral pixels within theperipheral area having the large size, but by using the pixel values ofthe peripheral objective pixels as the peripheral pixels having thepredetermined rate and selected from the peripheral pixels at random.Therefore, the noise can be effectively removed away while an increasein amount of arithmetic operation is suppressed.

As described above, with the noise removing device, a part of theperipheral pixels within the peripheral area having the large size isthinned out. Also, the filtering is carried out by using the pixelvalues of the peripheral objective pixels as the peripheral pixels afterthe thinning-out.

As a result, the artifact is generated in the image (post-noise removalimage) obtained through the filtering in the noise removal portion 26due to the thinning-out of the peripheral pixels, thereby reducing theimage quality.

The reduction of the image quality of the post-noise removal image dueto the artifact as described above is especially remarkable in a portionof a periodic pattern.

Then, the control portion 27 (refer to FIG. 2) suitably changes thesampling pattern representing the positions of the pixels which are tobe sampled at random.

That is to say, for example, in FIG. 3, the sampling pattern is changedevery marked pixel, in a word, every one pixel corresponding to theobjective image.

As a result, with the pixel thinning-out section 25, of the peripheralpixels whose pixel values are supplied from the peripheral pixelacquiring section 24, the peripheral pixels having the predeterminedrate are sampled at random in accordance with the pattern which differsevery pixel corresponding to the objective image, and the pixel valuesthereof are supplied as the pixel values of the peripheral objectivepixels to the noise removing portion 26.

As described above, when the sampling of the peripheral pixels iscarried out at random, and the pattern (sampling pattern) representingthe positions of the peripheral pixels which are to be sampled at randomis changed every one pixel corresponding to the objective image, theartifact is generated at random in the image (post-noise removal image)obtained through the filtering in the noise removing portion 26 (thecomponent of the artifact becomes random). Therefore, the artifactbecomes inconspicuous.

Therefore, in the noise removal for the image, the reduction of theimage quality due to the generation of the artifact generated owing tothe thinning-out can be readily prevented.

That is to say, even when although a suitable LPF is designed so as tosuppress the artifact, and the filtering by such an LPF is not carriedout, it is possible to prevent the reduction of the image quality due tothe generation of the artifact.

It is noted that the change of the sampling pattern can be carried outevery plural pixels instead of being carried out every one pixel.

In addition, in FIGS. 2 and 3, for ease of understanding, in theperipheral objective pixel random acquiring pattern 23, the peripheralpixel acquiring section 24 reads out the pixel values of the peripheralpixels within the peripheral area having the large size from the buffer21. After that, the pixel thinning-out section 25 samples the peripheralpixels within the peripheral area having the large size at random,thereby acquiring the peripheral objective pixels used for the filteringfor the noise removal. However, with the peripheral objective pixelrandom acquiring pattern 23, only the pixel values of the peripheralobjective pixels can be acquired by directly reading out only the pixelvalues of the peripheral objective pixels from the buffer 21.

In addition, in the case described above, the positions of the pixelscontained in the sampling pattern (the positions of the pixels which canbecome the positions represented by the sampling pattern) are notespecially limited, in a word, the peripheral pixels which can becomethe peripheral objective pixels are not especially limited. However, agiven limitation (hereinafter referred to as “a pattern limitation” aswell) can be imposed on the positions of the pixels contained in thesampling pattern.

With regard to the pattern limitation, for example, it is possible toadopt that the position(s) of the defect pixel(s) of the imaging element11 (refer to FIG. 1) is(are) contained in the sampling pattern about themarked pixel.

When it is adopted as the pattern limitation that the position(s) of thedefect position(s) is(are) not limited in the sampling pattern about themarked pixel, the control portion 27 acquires information on the defectpixel(s) of the imaging element 11, and sets the sampling pattern notcontaining therein the position(s) of (the peripheral pixel(s) becoming)the defect pixel(s) of the peripheral pixels within the peripheral areawith respect to the marked pixel.

In the case, it is possible to prevent the performance of the noiseremoval from being deteriorated due to the fact that the defect pixelbecomes the peripheral objective pixel, and is used for the filteringfor the noise terminal.

In addition, for example, it is possible to adopt as the patternlimitation that a part of the peripheral objective pixels acquired aboutthe last marked pixel is contained in the sampling pattern about themarked pixel.

When it is adopted as the pattern limitation that a part of theperipheral objective pixels acquired about the last marked pixel iscontained in the sampling pattern about the marked pixel, the controlportion 27 sets the sampling pattern containing therein the positions ofa part of the peripheral objective pixels acquired about the last markedpixel with respect to the current marked pixel.

In this case, a part of the peripheral objective pixels used for thefiltering for the noise removal with respect to the current marked pixel(hereinafter referred to as “the current peripheral objective pixel” aswell) is also the peripheral objective pixels used for the filtering forthe noise removal with respect to the last marked pixel (hereinafterreferred to as “the last peripheral objective pixel” as well). Also,when the processing for the last marked pixel is executed, the pixelvalues of the current peripheral objective pixels represented as thelast peripheral objective pixels as well are read out from the buffer21. When the processing for the current marked pixel is executed, thepixel values which are read out from the buffer 21 in a phase of theprocessing for the last marked pixel can be latched to be utilized, andthus need not to be read out from the buffer 21.

As a result, it is possible to reduce the number of accesses to thebuffer 21.

In addition thereto, for example, it is possible to adopt as the patternlimitation that the pixel whose position is represented by the samplingpattern about one pixel of the two pixels adjacent to each other, andthe pixel whose position is represented by the sampling pattern aboutthe other pixel do not overlap each other.

When it is adopted as the pattern limitation that the pixel whoseposition is represented by the sampling pattern about one pixel of thetwo pixels adjacent to each other, and the pixel whose position isrepresented by the sampling pattern about the other pixel do not overlapeach other, the control portion 27 sets the sampling patterns about thetwo pixels adjacent to each other in such a way that the pixel whoseposition is represented by the sampling pattern about one pixel of thetwo pixels adjacent to each other, and the pixel whose position isrepresented by the sampling pattern about the other pixel do not overlapeach other, that is, for example, in such a way that that the pixelwhose position is represented by the sampling pattern about one pixel ofthe two pixels adjacent to each other, and the pixel whose position isrepresented by the sampling pattern about the other pixel become aso-called nested state.

In this case, since with regard to the two pixels adjacent to eachother, the pixels becoming the peripheral objective pixels do notoverlap each other, the pixel values of the peripheral objective pixelsabout one pixel, and the pixel values of the peripheral objective pixelsabout the other pixel can be simultaneously read out from the buffer 21.Thus, when the two (or more) pieces of processing for the two (or more)pixel values of the two (or more) pixels are executed in parallel witheach other, the parallel processing can be executed at the high speed.

Here, when it is adopted as the pattern limitation that the position(s)of the defect position(s) is(are) not contained in the sampling patternabout the marked pixel, the control portion 27, for example, selects theperipheral pixels within the peripheral area at random, excludes (anyof) the defect pixel(s) from the peripheral pixels after the randomselection, and sets the sampling pattern representing the positions ofthe remaining peripheral pixels. Or, the control portion 27, forexample, excludes any of the defect pixels from the peripheral pixelswithin the peripheral area, selects the remaining peripheral pixels atrandom, and sets the sampling pattern representing the positions of theperipheral pixels after the random selection.

In addition, when it is adopted as the pattern limitation that theposition(s) of a part of the peripheral objective pixels acquired aboutthe last marked pixel is(are) contained in the sampling pattern aboutthe marked pixel, the control portion 27, for example, allocates a highprobability to the peripheral pixels set as the peripheral objectivepixels about the last marked pixel of the peripheral pixels within theperipheral area about the current marked pixel, and allocates a lowprobability to other peripheral pixels. Also, the control portion 27selects the peripheral pixels within the peripheral area about thecurrent marked pixel at random in accordance with the probabilities thusallocated, and sets the sampling pattern representing the positions ofthe peripheral pixels after the random selection.

Moreover, when it is adopted as the pattern limitation that the pixelwhose position is represented by the sampling pattern about one pixel ofthe two pixels adjacent to each other, and the pixel whose position isrepresented by the sampling pattern about the other pixel do not overlapeach other, the control portion 27, for example, selects the peripheralpixels within the peripheral area at random with respect to one pixel ofthe two pixels adjacent to each other, and sets the sampling patternrepresenting the positions of the peripheral pixels after the randomselection. Also, the control portion 27 excludes the peripheral pixelsselected (as the peripheral objective pixels) with respect to one pixelfrom the peripheral pixels within the peripheral area, selects theremaining peripheral pixels at random, and sets the sampling patternrepresenting the positions of the peripheral pixels after the randomselection.

It is noted that although in the foregoing, the still image is adoptedas the objective image, and the sampling pattern, for example, ischanged every one pixel corresponding to the objective image as thestill image in the control portion 27, the moving image can also beadopted as the objective image.

When the moving image is adopted as the objective image, with thecontrol portion 27, the sampling pattern can be changed every pixels, ofthe objective image as the moving image, arranged in a space direction,and every pixels arranged in a time direction.

In this case, the artifact becomes inconspicuous both in the spacedirection and in the time direction of the moving image, and thus withregard to the moving image, the reduction of the image quality due tothe generation of the artifact can be readily prevented.

[Noise Removing Processing]

FIG. 4 is a flow chart explaining noise removing processing executed bythe noise removing device shown in FIG. 2.

The image data is supplied from the preprocessing portion 12 to thenoise removing device, and is then stored as (the image data on) theobjective image as the object of the noise removal in the buffer 21.

When the image data on the objective image has been stored in the buffer21, the noise removing processing is started.

That is to say, in Step S11, the marked pixel acquiring portion 22selects the first pixel, for example, in the raster scanning order ofthe pixels each of which is not yet set as the marked pixel among of thepixels corresponding to the objective image whose pixel values arestored in the buffer 21 as the marked pixel, and acquires the markedpixel by reading out the pixel value of the marked pixel from the buffer21.

Also, the marked pixel acquiring portion 22 supplies the pixel value ofthe marked pixel acquired from the buffer 21 to the noise removingportion 26, and the operation then proceeds from the processing in StepS11 to processing in Step S12.

In Step S12, the control portion 27 sets the sampling pattern withrespect to the marked pixel, and supplies the data on the samplingpattern thus set to the peripheral objective pixel random acquiringportion 23. Then, the operation proceeds to processing in Step S13.

In Step S13, the peripheral objective pixel random acquiring portion 23acquires the pixel values of the peripheral pixels stored in the buffer21 in accordance with the sampling pattern the data on which is suppliedfrom the control portion 27 by reading out the pixel values of theperipheral pixels stored in the buffer 21 as the peripheral objectivepixels used for the filtering for the noise removal.

Also, the marked pixel acquiring portion 22 supplies the pixel values ofthe peripheral objective pixels acquired from the buffer 21 to the noiseremoving portion 26. Then, the operation proceeds from the processing inStep S13 to processing in Step S14.

In Step S14, the noise removing portion 26 carries out the filtering bythe ε filter with respect to the marked pixel by using both of the pixelvalue of the marked pixel supplied thereto from the marked pixelacquiring portion 22, and the pixel values of the peripheral objectivepixels supplied thereto from the peripheral objective pixel randomacquiring portion 23. Also, the noise removing portion 26 outputs theresulting pixel value obtained through the filtering as the pixel valueof the marked pixel of the post-noise removal image obtained by removingthe noise from the image signal of the objective image.

After that, the operation proceeds from the processing in Step S14 toprocessing in Step S15. In Step S15, the marked pixel acquiring portion22 determines whether or not all of the pixels corresponding to theobjective image whose pixel values are stored in the buffer 21 has beeneach set as the marked pixel.

When it is determined in Step S15 that the pixel(s) which is(are) notyet set as the marked pixel exists(exist) in the pixels corresponding tothe objective image whose pixel values are stored in the buffer 21, theoperation returns back to the processing S11. In Step S11, the markedpixel acquiring portion 22 selects the pixel next to the marked pixel inthe raster scanning order of the pixels corresponding to the objectiveimage whose pixel values are stored in the buffer 21 as the new markedpixel. This is repetitively followed by the same processing.

On the other hand, when it is determined in Step S15 that all of thepixels corresponding to the objective image whose pixel values arestored in the buffer 21 has been each set as the marked pixel, the noiseremoving processing is completed.

3. Second Embodiment [Second Configuration of Noise Removing Device]

FIG. 5 is a block diagram showing a second configuration of a noiseremoving device, as a portion (image processing device) for executingnoise removing processing according to a second embodiment of thepresent disclosure in the optical correcting portion 13 shown in FIG. 1.

It is noted that in FIG. 5, portions corresponding to those of the noiseremoving device shown in FIG. 2 are designated by the same referencenumerals, respectively, and a description thereof is suitably omittedfor the sake of simplicity.

With the noise removing device shown in FIG. 5, an image signal of anobjective image is divided into a low-frequency component and ahigh-frequency component in terms of the band. Also, a noise of an imagesignal of an image having the low-frequency component, and a noise of animage signal of an image having the high-frequency component are removedseparately from each other.

That is to say, with the noise removing device shown in FIG. 5, theimage signal of the objective image is supplied to each of an LPF 41 andan HPF 42.

The LPF 41 extracts a low-frequency component of an image signal of theobjective image by filtering the image signal of the objective imagethus supplied thereto, and supplies the image signal of the image of thelow-frequency component (hereinafter referred to as “the low-frequencycomponent image” as well) to the buffer 21.

Also, with the buffer 21 to the control portion 27, the same processingas that in the case of FIG. 2 is executed with the low-frequencycomponent image as an object. Also, the image signal of the resultingimage obtained by removing the noise from the image signal of thelow-frequency component image (hereinafter referred to as “thepost-noise removal low-frequency image” as well) is supplied from thenoise removing portion 26 to an image synthesizing portion 47.

On the other hand, the HPF 42 extracts a high-frequency component of theimage signal of the objective image by filtering the image signal of theobjective image thus supplied thereto, and supplies the image signal ofthe image of the high-frequency component (hereinafter referred to as“the high-frequency component image” as well) to the buffer 43.

Here, both of the LPF 41 and the HPF 42 are designed in such a way thatthe objective image is restored, for example, when the low-frequencycomponent image and the high-frequency component image are synthesizedwith each other.

The buffer 43 temporarily stores therein the image signal of thehigh-frequency component image supplied thereto from the HPF 42.

The marked pixel acquiring portion 44 selects each of the pixelscorresponding to the high-frequency component image whose image signalis stored in the buffer 43, for example, in the raster scanning ordersimilarly to the case of the marked pixel acquiring portion 22, acquiresthe pixel value of the marked pixel by reading out the pixel value ofthe marked pixel thus acquired to the noise removing portion 46.

The peripheral pixel acquiring portion 45 acquires all of the peripheralpixels within the peripheral area, for example, similar to the case ofthe peripheral objective pixel random acquiring portion 23 with respectto the marked pixel of the pixels corresponding to the high-frequencycomponent image whose image signals are stored in the buffer 43 as theperipheral objective pixels used for the filtering for the noiseremoval. Also, the peripheral pixel acquiring portion 45 supplies thepixel values of the peripheral objective images thus acquired to thenoise removing portion 46.

The noise removing portion 26, for example, is composed of atwo-dimensional median filter having a less amount of arithmeticoperation. Also, the noise removing portion 26 carried out the filteringfor the noise removal with respect to the marked pixel by using both ofthe pixel values of the marked pixel supplied thereto from the markedpixel acquiring portion 44, and the pixel values of the peripheralobjective pixels supplied thereto from the peripheral pixel acquiringportion 45. Also, the noise removing portion 26 supplies the resultingpixel value obtained through the filtering as the pixel value of themarked pixel corresponding to the image whose image signal is obtainedby removing the noise from the image signal of the high-frequency image(hereinafter referred to as “the post-noise removal high-frequencyimage” as well) to the image synthesizing portion 47.

The image synthesizing portion 47 synthesizes the post-noise removallow-frequency image from the noise removing portion 26, and thepost-noise removal high-frequency image from the noise removing portion46 with each other, and outputs the image signal of the resulting imageafter the synthesis as the image signal of the post-noise removal imageobtained by removing the noise from the image signal of the objectiveimage.

According to the noise removing device shown in FIG. 5, the image signalof the objective image is divided into the low-frequency component andthe high-frequency component in terms of the band by both of the LPF 41and the HPF 42, and the filtering for the noise removal is carried outby using the peripheral objective pixels sampled from the peripheralpixels within the peripheral area with respect to the image of thelow-frequency component (low-frequency component image). Therefore, itis possible to suppress the artifact due to the sampling (thinning-out).In addition, since the sampling of the peripheral objective pixel fromthe peripheral pixels is carried out at random with respect to thelow-frequency component image, even when the artifact is generated dueto the sampling, it is possible to prevent the artifact from beingconspicuous.

Therefore, the sampling of the peripheral objective pixel from theperipheral pixels is carried out at random with respect to thelow-frequency component image, whereby it is possible to prevent theartifact from being conspicuous. As a result, with regard to the designof the LPF 41, it is unnecessary to be severely conscious of suppressionof the artifact so much.

4. Third Embodiment [Program]

A program according to a third embodiment of the present disclosurecauses a computer to make a function so as to include: the peripheralobjective image random acquiring section 23 for acquiring the pixelsobtained by sampling the peripheral pixels located in the periphery ofthe marked pixel which is marked at random with respect to the markedpixel of the pixels corresponding to the objective image as the objectof the noise removal as the peripheral objective pixels as the pixelsused for filtering for noise removal; and the noise removing section 26for carrying out the filtering for the noise removal by using theperipheral objective pixels.

In the program of the third embodiment, the noise removing device of thefirst embodiment is applied. However, it goes without saying that thenoise removing device of the second embodiment can also applied to theprogram of the present disclosure.

5. Use Application [Description of Computer]

Next, the series of processing described above either can be executed byhardware or can be executed by software. When the series of processingdescribed above are executed by the software, the program composing thesoftware is installed in a general-purpose computer or the like.

Then, FIG. 6 shows an example of a configuration of the computer inwhich the program for executing the series of processing is installed.

The program can be previously recorded either in a hard disk 105 or in aROM 103 as a recording media built in the computer.

Or, the program can be stored (recorded) in a removable recording media111. Such a removable recording media 111 can be provided as so-calledpackage software. Here, a flexible disk, a Compact Disc Read Only Memory(CD-ROM), a Magneto Optical (MO) disk, a Digital versatile Disc (DVD), amagnetic disk, a semiconductor memory, or the like is given as theremovable recording media 111.

It is noted that in addition to the installing of the program from theremovable recording media 111 as described above in the computer, theprogram can be downloaded to the computer through either a communicationnetwork or a broadcasting network to be installed in the hard disk 105built in the computer. That is to say, the program, for example, eithercan be transferred from a download site to the computer in a wirelessmanner through an artificial satellite for a digital satellitebroadcasting or can be transferred to the computer in a wired mannerthrough a network such as a Local Area Network (LAN) or the Internet.

The computer has a Central Processing Unit (CPU) 102 built therein, andan I/O interface 110 is connected to the CPU 102 through a bus 101.

When an instruction is inputted to the CPU 102 through the I/O interface110 by manipulating the inputting portion 109 by a user, the CPU 102executes the program stored in a Read Only Memory (ROM) 103 inaccordance with the instruction thus inputted. Or, the CPU 102 loads theprogram stored in the hard disk 105 into a Random Access Memory (RAM)104, thereby executing the program.

As a result, the CPU 102 executes either the processing complying withthe flow chart described above, or the processing based on theconfiguration of the block diagram described above. Also, the CPU 102,for example, outputs the processing result from an outputting portion106 through the I/O interface 110, transmits the processing result fromthe communication portion 108, or records the processing result in thehard disk 105 as may be necessary.

It is noted that the inputting portion 107 is composed of a keyboard, amouse, a microphone or the like. In addition, the outputting portion 106is composed of a Liquid Crystal Display (LCD) device, a speaker or thelike.

Here, in this specification, the processing which the computer executesin accordance with the program is not necessarily executed in a timeseries manner along the order described in the form of the flow chart.That is to say, the processing which the computer executes in accordancewith the program also includes predetermined pieces of processing aswell which are executed in parallel or independently (such as theparallel processing or the processing by an object).

In addition, the program may be processed by one computer (processor) ormay be distributively processed by plural computers. Moreover, theprogram may be transferred to a remote computer to be executed.

It should be noted that the embodiments of the present disclosure are byno means limited to the embodiments described above, and various kindsof changes can be made without departing from the subject matter of thepresent disclosure.

That is to say, in the embodiments of the present disclosure, when theshutter speed of the digital camera, for example, is set to the highspeed, and thus the S/N ratio of the objective image is remarkablydeteriorated, the filtering for the noise removal is carried out byusing the peripheral pixels (peripheral objective pixels) having thepredetermined rate selected from the peripheral pixels within theperipheral area having the large size at random. However, the filteringusing the peripheral pixels having the predetermined rate and selectedfrom the peripheral pixels within the peripheral area having the largesize at random can be carried out for the image in which the S/N ratiois not deteriorated so much.

In addition, the image data for the noise removing processing is by nomeans limited to the RAW data. That is to say, the noise removingprocessing, for example, can be executed for the image data, such as aluminance signal Y, and color difference signals Cb and Cr, other thanthe RAW data.

In addition, in the embodiments described above, with the opticalcorrecting portion 13, the noise removing processing is executed for theimage data supplied from the preprocessing portion 12. In additionthereto, however, the noise removing processing, for example, can beexecuted at a timing right before or right after the de-mosaicprocessing, or right after the gamma correcting processing in the signalprocessing portion 14.

In addition, the present disclosure can be applied to an apparatus ordevice for processing an image such as a television receiver (TV) inaddition to the digital camera.

The present disclosure contains subject matter related to that disclosedin Japanese Priority Patent Application JP 2010-275819 filed in theJapan Patent Office on Dec. 10, 2010, the entire content of which ishereby incorporated by reference.

It should be understood by those skilled in the art that variousmodifications, combinations, sub-combinations and alterations may occurdepending on design requirements and other factors insofar as they arewithin the scope of the appended claims or the equivalents thereof.

1. An image processing device, comprising: a peripheral objective pixelrandom acquiring section acquiring pixels obtained by samplingperipheral pixels located in a periphery of a marked pixel which ismarked at random with respect to the marked pixel of pixelscorresponding to an objective image as an object of noise removal asperipheral objective pixels as pixels used for filtering for noiseremoval; and a noise removing section carrying out filtering for thenoise removal by using the peripheral objective pixels.
 2. The imageprocessing device according to claim 1, further comprising: a settingsection setting a sampling pattern representing positions of the pixelswhich are to be sampled at random, wherein said setting section changesthe sampling pattern every pixel of the objective image, and saidperipheral objective pixel random acquiring section acquires theperipheral objective pixels in accordance with the sampling pattern. 3.The image processing device according to claim 2, wherein the objectiveimage is an image outputted by an imaging element capturing an image,and said setting section sets the sampling pattern not containingtherein a position of a defect pixel of said imaging element.
 4. Theimage processing device according to claim 2, wherein said settingsection sets the sampling pattern containing therein a position of apart of the peripheral objective pixels acquired about the last markedpixel with respect to the marked pixel.
 5. The image processing deviceaccording to claim 2, wherein said setting section sets the samplingpattern in such a way that a pixel whose position is represented by thesampling pattern about one pixel of two pixels adjacent to each other,and a pixel whose position is represented by the sampling pattern aboutthe other pixel do not overlap each other.
 6. The image processingdevice according to claim 1, further comprising: a setting sectionsetting a sampling pattern representing positions of the pixels whichare to be sampled at random, wherein the objective image is a movingimage, said setting section changes the sampling pattern every pixelsarranged in a space direction and every pixels arranged in a timedirection, and said peripheral objective pixel random acquiring sectionacquires the peripheral objective pixels in accordance with the samplingpattern.
 7. The image processing device according to claim 1, furthercomprising: a low-frequency component extracting section extracting alow-frequency component of the objective image; a high-frequencycomponent extracting section extracting a high-frequency component ofthe objective image; a noise removing section for a high-frequencycomponent carrying out filtering for noise removal about an image of thehigh-frequency component; and a synthesizing section synthesizing thelow-frequency component and the high-frequency component with eachother, wherein said peripheral objective pixel random acquiring sectionacquires the peripheral objective pixels from an image corresponding tothe low-frequency component, said noise removing section carries outfiltering for noise removal about the image corresponding to thelow-frequency component by using the peripheral objective pixelsacquired from the image corresponding to the low-frequency component,and said synthesizing section synthesizes the low-frequency componentafter the noise removal obtained through the filtering in said noiseremoving section, and the high-frequency component after the noiseremoval obtained through the filtering in said noise removing sectionfor a high-frequency component with each other.
 8. An image processingmethod, comprising: acquiring pixels obtained by sampling peripheralpixels located in a periphery of a marked pixel which is marked atrandom with respect to the marked pixel of pixels corresponding to anobjective image as an object of noise removal as peripheral objectivepixels as pixels used for filtering for noise removal by an imageprocessing device; and carrying out filtering for the noise removal byusing the peripheral objective pixels by said image processing device.9. A program causing a computer to make a function so as to comprise: aperipheral objective pixel random acquiring section acquiring pixelsobtained by sampling peripheral pixels located in a periphery of amarked pixel which is marked at random with respect to the marked pixelof pixels corresponding to an objective image as an object of noiseremoval as peripheral objective pixels as pixels used for filtering fornoise removal; and a noise removing section carrying out filtering forthe noise removal by using the peripheral objective pixels.